course | Data Management - Mid Level

Understanding Data Management

Module 1: What Data Management Really Means

• Data management vs. data analysis
• Why data issues persist in organizations
• Business impact of poor data management

Module 2: Data as an Organizational Asset

• Data value and lifecycle
• Treating data like any other asset
• Balancing accessibility and control

Data Quality and Reliability

Module 3: Core Data Quality Dimensions

• Accuracy, completeness, consistency, timeliness
• Common sources of data quality issues
• Identifying quality gaps

Module 4: Improving Data Quality in Practice

• Preventing errors at the source
• Standardization and validation practices
• Continuous quality monitoring

Data Ownership and Governance

Module 5: Data Ownership and Accountability

• Roles: data owner, data user, data steward
• Responsibility vs. access
• Escalation and issue resolution

Module 6: Data Governance Basics

• Policies, standards, and controls
• Aligning governance with business needs
• Avoiding over-governance

Managing Data Across Processes

Module 7: Data Flow Across Systems and Processes

• Data handoffs and dependencies
• Integration challenges
• Preventing duplication and inconsistency

Module 8: Managing Data Changes

• Handling updates and corrections
• Version control and documentation
• Managing change impact

Risk, Compliance, and Continuous Improvement

Module 9: Data Risk and Compliance Awareness

• Regulatory and internal requirements
• Managing sensitive and regulated data
• Reducing exposure and risk

Module 10: Sustaining Effective Data Management

• Continuous improvement mindset
• Measuring data management performance
• Embedding data discipline into daily work